Security Researcher, Cynet Security

• 5+ years of hands-on cybersecurity research experience
• Proven experience working with EDR, malware analysis, threat detection, and security tooling
• Proficiency in C, C++, and Python with strong debugging abilities
• Solid understanding of Windows internals, including low-level OS concepts
• Experience with static and dynamic analysis, reverse engineering, and real-world threat investigations
• A scientific, data-driven approach to problem-solving, from ideation through experimentation and production
• Strong understanding of statistical concepts and ML feature engineering techniques
• Experience analyzing large-scale datasets using SQL, Spark, or similar tools

Desirable

• This is a role for someone who wants to put their soul into their craft, someone hungry to learn fast, experiment boldly, and turn ambitious ideas into production-ready AI solutions
• Drive innovation by combining deep security research with modern AI techniques to build impactful, customer-facing security capabilities
• Build and refine intelligent generative AI agents that drive automated cybersecurity reasoning, investigation workflows, and threat analysis
• Extend and enhance our next-generation AI antivirus engine by designing new feature representations, building file parsers, and developing ML models end-to-end
• Engineer and implement core parser and model components in C++ and Python to seamlessly integrate into the Cynet Endpoint Agent and platform infrastructure
• Use Cynet’s ML experimentation pipelines to run experiments, optimize performance, and deliver production-ready detection models
• Serve as the cybersecurity expert within the Data Science team, guiding threat modeling, malware understanding, and security-driven AI design decisions